Application of Face Detection for Learning Engagement in Classroom

Integrating artificial intelligence (AI) and education has led to the widespread application of facial recognition technology in various fields, including classroom teaching. In this project, AI methods are used to acquire facial expression data of students to create an effective classroom state evaluation mechanism that assists teachers in improving the quality and efficiency of classroom teaching. The research involves analyzing the significance of the application of face detection technology in classroom teaching, constructing a face detection dataset based on the classroom environment, and identifying critical methods used in classroom teaching application systems. The proposed face detection system for teaching in the classroom improves traditional face detection algorithms by optimizing the network structure and implementing a lightweight classroom monitoring program to evaluate each student's classroom status. The real-time detection of students' facial expressions provides teachers with timely feedback to enhance teaching quality and learning engagement in the classroom.